css-color-names
A JSON object mapping every standard CSS color name to its hex value, ready to require() and use directly.
Repository Health
Technical Analysis
css-color-names is a minimal npm package that exports a single JSON object pairing every standard CSS color keyword (aqua, aliceblue, antiquewhite, and so on) with its corresponding hex color code. The dataset is generated by scraping a reference color list and normalizing it into a flat, lowercase key-value structure, so consumers get a ready-to-use lookup table without maintaining their own copy of the CSS color specification.
The package declares no runtime dependencies and requires no build step for consumers — requiring the module returns the JSON object directly. It’s the kind of small data package that other color-parsing or color-conversion libraries pull in when they need to resolve a named CSS color like “tomato” or “cornflowerblue” into its hex representation.
What You Get
- Complete CSS color map - A JSON object covering the standard CSS extended color keywords mapped to their hex codes.
- Zero-dependency require -
require('css-color-names')returns the plain object directly, with no runtime dependencies to install. - Regeneration scripts -
getcolors.shandstringify.jslet maintainers rebuild the JSON from the canonical W3Schools color list viamake. - Predictable lowercase keys - Color names are normalized to lowercase before being written out, so lookups don’t need case handling.
Common Use Cases
- Resolving named colors in a color-parsing library - Convert a user-supplied CSS color keyword like “tomato” into a hex code for downstream color math.
- Building a color picker UI - Populate a swatch list or autocomplete dropdown with every valid CSS color name and its hex value.
- Validating CSS color keywords - Check whether a string is a real CSS color name by testing for key presence in the object.
- Generating design tokens - Use the map as a seed dataset when generating a design system’s named color tokens.
Under The Hood
Architecture
There isn’t really an execution path to trace: the package’s main field points straight at css-color-names.json, so require('css-color-names') returns the static object with no wrapper code or runtime logic in between. The only “architecture” is the offline generation pipeline described by the Makefile, which pipes getcolors.sh (a shell script that scrapes a reference color-name page) into stringify.js (a tiny Node script that turns newline-separated name hex pairs into a JSON object). Nothing in the consumer-facing surface would break from a refactor, because there is no abstraction layer to change — the data file is the entire public interface.
Tech Stack
The generation tooling mixes Bash (getcolors.sh, using curl, sed, awk, and tr to scrape and normalize the source page) with a small vanilla Node.js script (stringify.js, using only the built-in fs module) and a Makefile to orchestrate the two. package.json declares empty dependencies, devDependencies, and optionalDependencies objects — there is no build tool, bundler, or framework anywhere in the stack. Distribution is a single JSON file published to npm under the main field.
Code Quality
No test files exist anywhere in the repository, despite package.json defining a test script that iterates tests/*.js — since that directory doesn’t exist, running npm test would loop over zero files and print “Passed!” without exercising anything. There is no linter, formatter, or CI configuration in the repo. The generation scripts do no input validation or error handling around the scrape step. Given the package is static data with no runtime logic, the absence of tests and typing has limited practical impact, but it also means the generation pipeline itself is unverified.
What Makes It Unique
The package isn’t technically novel — several other npm packages (e.g. color-name) ship comparable name-to-hex maps, and a flat JSON lookup table is about as standard a data shape as exists. Its only distinguishing trait is that it documents its own generation process end-to-end (scrape script, conversion script, and Makefile all committed to the repo), making the dataset’s provenance reproducible rather than opaque.